학술논문

Sea-Ice Permittivity Derived From GNSS Reflection Profiles: Results of the MOSAiC Expedition
Document Type
Periodical
Source
IEEE Transactions on Geoscience and Remote Sensing IEEE Trans. Geosci. Remote Sensing Geoscience and Remote Sensing, IEEE Transactions on. 60:1-16 2022
Subject
Geoscience
Signal Processing and Analysis
Sea ice
Arctic
Sea measurements
Permittivity
Global navigation satellite system
Temperature measurement
Ocean temperature
Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition
reflectometry
satellite navigation systems
sea-ice permittivity
Language
ISSN
0196-2892
1558-0644
Abstract
Reflectometry measurements have been conducted aboard the German research icebreaker Polarstern during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. Signals of Global Navigation Satellite Systems (GNSS) were recorded using a dedicated GNSS reflectometry receiver for retrieval of sea-ice reflectivity. The primary goal is reflectometry-based monitoring of sea ice as a part of the Arctic climate study. The dataset presented here covers the expedition’s first leg (late September to mid-December 2019) in the Siberian Sector of the central Arctic (at about 82 ° N to $87~^\circ $ N). Daily profiles of reflectivity are retrieved for satellite elevations $< 45^\circ $ . In agreement with model prediction, the results show best reflectivity contrast (about 5 dB between compact pack-ice and lower ice concentrations) for observations at left-handed circular polarization and elevation angles of 10°–20°. A daily resolved time series of sea-ice relative permittivity is inverted from the left-handed data. In general, the level of inversion results is at the lower limit of sea-ice values (relative permittivity of 3 and below), potentially indicating an influence of incoherent volume scattering. An occasional increase in the relative permittivity is attributed to the presence of water. Sea-ice profiles show anomalies that are confirmed by enhanced model prediction (slab reflection). A long-term comparison of prediction and retrieved profiles indicates anomalies’ dependence on ice thickness and temperature.